• DocumentCode
    1563505
  • Title

    A Modified Particle Swarm Optimization Algorithm

  • Author

    Shuhua, Wen ; Xueliang, Zhang ; Hainan, Li ; Shuyang, Liu ; Jiaying, Wang

  • Author_Institution
    Taiyuan Univ. of Sci. & Technol.
  • Volume
    1
  • fYear
    2005
  • Firstpage
    318
  • Lastpage
    321
  • Abstract
    A modified particle swarm optimization (MPSO) algorithm is presented based on the variance of the population´s fitness. During computing, the inertia weight of MPSO is determined adaptively and randomly according to the variance of the populations fitness. And the ability of , particle swarm optimization algorithm (PSO) to break away from the local optimum is greatly improved. The simulating results show that this algorithm not only has great advantage of convergence property over standard simple PSO, but also can avoid the premature convergence problem effectively
  • Keywords
    particle swarm optimisation; convergence property; modified particle swarm optimization; populations fitness; Birds; Computational modeling; Convergence; Educational institutions; Evolutionary computation; Genetic algorithms; Genetic mutations; Marine animals; Particle swarm optimization; Particle tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks and Brain, 2005. ICNN&B '05. International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7803-9422-4
  • Type

    conf

  • DOI
    10.1109/ICNNB.2005.1614623
  • Filename
    1614623